Stochastic noises of fiber optic gyroscope （FOG） mainly contain white noise and fractal noise whose long-term dependent component causes FOG a rather slow drift. In order to eliminate this component, a two-step filt...Stochastic noises of fiber optic gyroscope （FOG） mainly contain white noise and fractal noise whose long-term dependent component causes FOG a rather slow drift. In order to eliminate this component, a two-step filtering methodology is proposed. Firstly, fractional differencing （FD） method is introduced to trans-form fractal noise into fractional white noise based on the estima-tion of Hurst exponent for long-term dependent fractal process, which together with the existing white noise make up of a gener-alized white noise. Further, an improved denoising algorithm of wavelet maxima is developed to suppress the generalized white noise. Experimental results show that the basic noise terms of FOG greatly decrease, and especially the slow drift is restrained effectively. The proposed methodology provides a promising ap-proach for filtering long-term dependent fractal noise.展开更多
Aiming at the problems of low measurement accuracy,uncertainty and nonlinearity of random noise of the micro electro mechanical system(MEMS)gyroscope,a gyroscope noise estimation and filtering method is proposed,which...Aiming at the problems of low measurement accuracy,uncertainty and nonlinearity of random noise of the micro electro mechanical system(MEMS)gyroscope,a gyroscope noise estimation and filtering method is proposed,which combines expectation maximum(EM)with maximum a posterior(MAP)to form an adpative unscented Kalman filter(UKF),called EMMAP-UKF.According to the MAP estimation principle,a suboptimal unbiased MAP noise statistical estimation model is constructed.Then,EM algorithm is introduced to transform the noise estimation problem into the mathematical expectation maximization problem,which can dynamically adjust the variance of the observed noise.Finally,the estimation and filtering of gyroscope random drift error can be realized.The performance of the gyro noise filtering method is evaluated by Allan variance,and the effectiveness of the method is verified by hardware-in-the-loop simulation.展开更多
In order to suppress the noise of gyroscopes,the method based on lock-in amplifier and capacitor matching of the low-noise readout circuit is proposed. Firstly,the principle to suppress the noise by lock-in amplifier ...In order to suppress the noise of gyroscopes,the method based on lock-in amplifier and capacitor matching of the low-noise readout circuit is proposed. Firstly,the principle to suppress the noise by lock-in amplifier is analyzed,and the noise model of front end is proposed. Secondly,the noise optimization for the charge amplifier is presented according to the noise model of front end. Finally,a readout circuit is constructed by this approach. The measurement results show that the parasitic capacitance of front end is 18 p F,and the noise at resonant frequency( 4 k Hz) is 133 n V / Hz1 / 2,and the overall bias stability is 30° /h,and the noise level is 0. 003° /( s·Hz1 / 2). The noise of the gyroscope with the low-noise readout by this method is suppressed effectively.展开更多
By the sketch of structure of MVWG,the working laws of this kind of gyroscope we re explained.To the aid of Euler′s Dynamics Equation,a mathematical model of the gyroscope was constructed,and then by the basic workin...By the sketch of structure of MVWG,the working laws of this kind of gyroscope we re explained.To the aid of Euler′s Dynamics Equation,a mathematical model of the gyroscope was constructed,and then by the basic working laws of MVWG the model was simplified.Under the conditions of the three axial direction rotations and general rotation,the mathematical model was resolved.And finally by the solutions, the working laws of the gyroscope, the working disparity among all sorts of gyrations and the influences from the gyrations in the axial directions were analysed.展开更多
Ambient noise tomography,when applied to a dense linear seismic array,has the capability to provide detailed insights into the fine velocity structures across diverse tectonic settings.The linear station arrangement n...Ambient noise tomography,when applied to a dense linear seismic array,has the capability to provide detailed insights into the fine velocity structures across diverse tectonic settings.The linear station arrangement naturally generates parallel and concentrated ray paths along the array trend.This unique geometry requires specific optimization of the inversion methodology and model parameterization.The Bayesian-based transdimensional inversion method,characterized by its fully non-linear nature and high degree of freedom in parameter settings,offers a powerful tool for ambient noise inversion.To effectively adapt this method to a linear array layout,we propose a modification to the Voronoi cell tessellation built in the transdimensional method.By introducing spatial priority to the Voronoi kernels,we strategically increased the density of Voronoi cells along the direction of the array.We then applied the modified approach to a linear seismic array in the North China Craton and validated its robustness through phase velocity images and resolution tests.Our improved non-uniform sampling technique in the 2-D model space accelerates convergence while simultaneously enhancing model accuracy.Compared with the conventional damped leastsquares method,the proposed algorithm revealed a shear-wave velocity map with notable low-velocity anomalies situated in the middle and lower crust beneath the borders of the Ordos block and its surrounding orogenic belt.Aligned with the crustal structures revealed by receiver function and electrical imaging,our findings indicated that the western and eastern margins of the Ordos block had experienced intensive crustal wedge deformation and re-melting,respectively.展开更多
Turbine noise would be one of the dominant noise sources especially in future UHBR (Ultra High Bypass-Ratio) aeroengine, but its currently far from being studied enough. Acoustic mode is crucial for duct propagation b...Turbine noise would be one of the dominant noise sources especially in future UHBR (Ultra High Bypass-Ratio) aeroengine, but its currently far from being studied enough. Acoustic mode is crucial for duct propagation but little study about the relation between serration and mode. Thus, taking axial single-turbine test bench NPU-Turb as object, the effect of Stator with Serrated Trailing-edge (Bionic S) and Rotor with Serrated Leading-edge (Bionic R) on duct acoustic modes of turbine turbulence interac-tion noise were studied in detail using DDES/AA hybrid model validated by acoustic experiment of NPU-Turb. Serval conclusions can be made here. First, for broadband noise, the effect of serrations on duct modes (increased or reduced of PWL<sub>mn</sub>) with the increasing frequency is more prominent. Second, the changing trend of ?PWL<sub>mn</sub> is something like Chinese character “人” with circumferential mode m and alternating with radial mode. Such distribution is more obvious at higher frequency. More theoretical and mechanistic research work needs to be carried out in depth in the future. .展开更多
Parkinson’s disease manifests in movement disorder symptoms, such as hand tremor. There exists an assortment of therapy interventions. In particular deep brain stimulation offers considerable efficacy for the treatme...Parkinson’s disease manifests in movement disorder symptoms, such as hand tremor. There exists an assortment of therapy interventions. In particular deep brain stimulation offers considerable efficacy for the treatment of Parkinson’s disease. However, a considerable challenge is the convergence toward an optimal configuration of tuning parameters. Quantified feedback from a wearable and wireless system consisting of an accelerometer and gyroscope can be enabled through a novel software application on a smartphone. The smartphone with its internal accelerometer and gyroscope can record the quantified attributes of Parkinson’s disease and tremor through mounting the smartphone about the dorsum of the hand. The recorded data can be then wirelessly transmitted as an email attachment to an Internet derived resource for subsequent post-processing. The inertial sensor data can be consolidated into a feature set for machine learning classification. A multilayer perceptron neural network has been successfully applied to attain considerable classification accuracy between deep brain stimulation “On” and “Off” scenarios for a subject with Parkinson’s disease. The findings establish the foundation for the broad objective of applying wearable and wireless systems for the development of closed-loop optimization of deep brain stimulation parameters in the context of cloud computing with machine learning classification.展开更多
Deconvolution denoising in the f-x domain has some defects when facing situations like complicated geology structure, coherent noise of steep dip angles, and uneven spatial sampling. To solve these problems, a new fil...Deconvolution denoising in the f-x domain has some defects when facing situations like complicated geology structure, coherent noise of steep dip angles, and uneven spatial sampling. To solve these problems, a new filtering method is proposed, which uses the generalized S transform which has good time-frequency concentration criterion to transform seismic data from the time-space to time-frequency-space domain （t-f-x）. Then in the t-f-x domain apply Empirical Mode Decomposition （EMD） on each frequency slice and clear the Intrinsic Mode Functions （IMFs） that noise dominates to suppress coherent and random noise. The model study shows that the high frequency component in the first IMF represents mainly noise, so clearing the first IMF can suppress noise. The EMD filtering method in the t-f-x domain after generalized S transform is equivalent to self-adaptive f-k filtering that depends on position, frequency, and truncation characteristics of high wave numbers. This filtering method takes local data time-frequency characteristic into consideration and is easy to perform. Compared with AR predictive filtering, the component that this method filters is highly localized and contains relatively fewer low wave numbers and the filter result does not show over-smoothing effects. Real data processing proves that the EMD filtering method in the t-f-x domain after generalized S transform can effectively suppress random and coherent noise of steep dips.展开更多
Long-time cross correlation of ambient noise has been proved as a powerful tool to extract Green＇s function between two receivers. The study of composition of ambient noise is important for a better understanding of ...Long-time cross correlation of ambient noise has been proved as a powerful tool to extract Green＇s function between two receivers. The study of composition of ambient noise is important for a better understanding of this method. Previous studies confirm that ambient noise in the long period （3 s and longer） mostly consists of surface wave, and 0.25-2.5 s noise consists more of body waves. In this paper, we perform cross correlation processing at much higher frequency （30-70 Hz） using ambient noise recorded by a small aperture array. No surface waves emerge from noise correlation function （NCF）, but weak P waves emerge. The absence of surface wave in NCF is not due to high attenuation since surface waves are strong from active source, therefore probably the high ambient noise mostly consists of body wave and lacks surface wave. Origin of such high frequency body waves in ambient noise remains to be studied.展开更多
Because ambient seismic noise provides estimated Green’s function （EGF） between two sites with high accuracy, Rayleigh wave propagation along the path connecting the two sites is well resolved. Therefore, earthquak...Because ambient seismic noise provides estimated Green’s function （EGF） between two sites with high accuracy, Rayleigh wave propagation along the path connecting the two sites is well resolved. Therefore, earthquakes which are close to one seismic station can be well located with calibration extracting from EGF. We test two algorithms in locating the 1998 Zhangbei earthquake, one algorithm is waveform-based, and the other is traveltime-based. We first compute EGF between station ZHB （a station about 40 km away from the epicenter） and five IC/IRIS stations. With the waveform-based approach, we calculate 1D synthetic single-force Green’s functions between ZHB and other four stations, and obtain traveltime corrections by correlating synthetic Green’s functions with EGFs in period band of 10–30 s. Then we locate the earthquake by minimizing the differential travel times between observed earthquake waveform and the 1D synthetic earthquake waveforms computed with focal mechanism provided by Global CMT after traveltime correction from EGFs. This waveform-based approach yields a location which error is about 13 km away from the location observed with InSAR. With the traveltime-based approach, we begin with measuring group velocity from EGFs as well as group arrival time on observed earthquake waveforms, and then locate the earthquake by minimizing the difference between observed group arrival time and arrival time measured on EGFs. This traveltime-based approach yields accuracy of 3 km, Therefore it is feasible to achieve GT5 （ground truth location with accuracy 5 km） with ambient seismic noises. The less accuracy of the waveform-based approach was mainly caused by uncertainty of focal mechanism.展开更多
The method of extracting Green＇s function between stations from cross correlation has proven to be effective theoretically and experimentally. It has been widely applied to surface wave tomography of the crust and up...The method of extracting Green＇s function between stations from cross correlation has proven to be effective theoretically and experimentally. It has been widely applied to surface wave tomography of the crust and upmost mantle. However, there are still controversies about why this method works. Snieder employed stationary phase approximation in evaluating contribution to cross correlation function from scatterers in the whole space, and concluded that it is the constructive interference of waves emitted by the scatterers near the receiver line that leads to the emergence of Green＇s function. His derivation demonstrates that cross correlation function is just the convolution of noise power spectrum and the Green＇s function. However, his derivation ignores influence from the two stationary points at infinities, therefore it may fail when attenuation is absent. In order to obtain accurate noise-correlation function due to scatters over the whole space, we compute the total contribution with numerical integration in polar coordinates. Our numerical computation of cross correlation function indicates that the incomplete stationary phase approximation introduces remarkable errors to the cross correlation function, in both amplitude and phase, when the frequency is low with reasonable quality factor Q. Our results argue that the dis- tance between stations has to be beyond several wavelengths in order to reduce the influence of this inaccuracy on the applications of ambient noise method, and only the station pairs whose distances are above several （〉5） wavelengths can be used.展开更多
基金supported by Aviation Science Foundation(20070851011).
文摘Stochastic noises of fiber optic gyroscope （FOG） mainly contain white noise and fractal noise whose long-term dependent component causes FOG a rather slow drift. In order to eliminate this component, a two-step filtering methodology is proposed. Firstly, fractional differencing （FD） method is introduced to trans-form fractal noise into fractional white noise based on the estima-tion of Hurst exponent for long-term dependent fractal process, which together with the existing white noise make up of a gener-alized white noise. Further, an improved denoising algorithm of wavelet maxima is developed to suppress the generalized white noise. Experimental results show that the basic noise terms of FOG greatly decrease, and especially the slow drift is restrained effectively. The proposed methodology provides a promising ap-proach for filtering long-term dependent fractal noise.
基金National Natural Science Foundation of China(No.61863024)Scientific Research Projects of Higher Institutions of Gansu Province(No.2018C-11)+1 种基金Natural Science Foundation of Gansu Province(No.18JR3RA107)Science and Technology Program of Gansu Province(No.18CX3ZA004)。
文摘Aiming at the problems of low measurement accuracy,uncertainty and nonlinearity of random noise of the micro electro mechanical system(MEMS)gyroscope,a gyroscope noise estimation and filtering method is proposed,which combines expectation maximum(EM)with maximum a posterior(MAP)to form an adpative unscented Kalman filter(UKF),called EMMAP-UKF.According to the MAP estimation principle,a suboptimal unbiased MAP noise statistical estimation model is constructed.Then,EM algorithm is introduced to transform the noise estimation problem into the mathematical expectation maximization problem,which can dynamically adjust the variance of the observed noise.Finally,the estimation and filtering of gyroscope random drift error can be realized.The performance of the gyro noise filtering method is evaluated by Allan variance,and the effectiveness of the method is verified by hardware-in-the-loop simulation.
文摘In order to suppress the noise of gyroscopes,the method based on lock-in amplifier and capacitor matching of the low-noise readout circuit is proposed. Firstly,the principle to suppress the noise by lock-in amplifier is analyzed,and the noise model of front end is proposed. Secondly,the noise optimization for the charge amplifier is presented according to the noise model of front end. Finally,a readout circuit is constructed by this approach. The measurement results show that the parasitic capacitance of front end is 18 p F,and the noise at resonant frequency( 4 k Hz) is 133 n V / Hz1 / 2,and the overall bias stability is 30° /h,and the noise level is 0. 003° /( s·Hz1 / 2). The noise of the gyroscope with the low-noise readout by this method is suppressed effectively.
文摘By the sketch of structure of MVWG,the working laws of this kind of gyroscope we re explained.To the aid of Euler′s Dynamics Equation,a mathematical model of the gyroscope was constructed,and then by the basic working laws of MVWG the model was simplified.Under the conditions of the three axial direction rotations and general rotation,the mathematical model was resolved.And finally by the solutions, the working laws of the gyroscope, the working disparity among all sorts of gyrations and the influences from the gyrations in the axial directions were analysed.
基金funded by the Special Fund of the Institute of Geophysics,China Earthquake Administration (Nos.DQJB21K52,and DQJB22R33)。
文摘Ambient noise tomography,when applied to a dense linear seismic array,has the capability to provide detailed insights into the fine velocity structures across diverse tectonic settings.The linear station arrangement naturally generates parallel and concentrated ray paths along the array trend.This unique geometry requires specific optimization of the inversion methodology and model parameterization.The Bayesian-based transdimensional inversion method,characterized by its fully non-linear nature and high degree of freedom in parameter settings,offers a powerful tool for ambient noise inversion.To effectively adapt this method to a linear array layout,we propose a modification to the Voronoi cell tessellation built in the transdimensional method.By introducing spatial priority to the Voronoi kernels,we strategically increased the density of Voronoi cells along the direction of the array.We then applied the modified approach to a linear seismic array in the North China Craton and validated its robustness through phase velocity images and resolution tests.Our improved non-uniform sampling technique in the 2-D model space accelerates convergence while simultaneously enhancing model accuracy.Compared with the conventional damped leastsquares method,the proposed algorithm revealed a shear-wave velocity map with notable low-velocity anomalies situated in the middle and lower crust beneath the borders of the Ordos block and its surrounding orogenic belt.Aligned with the crustal structures revealed by receiver function and electrical imaging,our findings indicated that the western and eastern margins of the Ordos block had experienced intensive crustal wedge deformation and re-melting,respectively.
文摘Turbine noise would be one of the dominant noise sources especially in future UHBR (Ultra High Bypass-Ratio) aeroengine, but its currently far from being studied enough. Acoustic mode is crucial for duct propagation but little study about the relation between serration and mode. Thus, taking axial single-turbine test bench NPU-Turb as object, the effect of Stator with Serrated Trailing-edge (Bionic S) and Rotor with Serrated Leading-edge (Bionic R) on duct acoustic modes of turbine turbulence interac-tion noise were studied in detail using DDES/AA hybrid model validated by acoustic experiment of NPU-Turb. Serval conclusions can be made here. First, for broadband noise, the effect of serrations on duct modes (increased or reduced of PWL<sub>mn</sub>) with the increasing frequency is more prominent. Second, the changing trend of ?PWL<sub>mn</sub> is something like Chinese character “人” with circumferential mode m and alternating with radial mode. Such distribution is more obvious at higher frequency. More theoretical and mechanistic research work needs to be carried out in depth in the future. .
文摘Parkinson’s disease manifests in movement disorder symptoms, such as hand tremor. There exists an assortment of therapy interventions. In particular deep brain stimulation offers considerable efficacy for the treatment of Parkinson’s disease. However, a considerable challenge is the convergence toward an optimal configuration of tuning parameters. Quantified feedback from a wearable and wireless system consisting of an accelerometer and gyroscope can be enabled through a novel software application on a smartphone. The smartphone with its internal accelerometer and gyroscope can record the quantified attributes of Parkinson’s disease and tremor through mounting the smartphone about the dorsum of the hand. The recorded data can be then wirelessly transmitted as an email attachment to an Internet derived resource for subsequent post-processing. The inertial sensor data can be consolidated into a feature set for machine learning classification. A multilayer perceptron neural network has been successfully applied to attain considerable classification accuracy between deep brain stimulation “On” and “Off” scenarios for a subject with Parkinson’s disease. The findings establish the foundation for the broad objective of applying wearable and wireless systems for the development of closed-loop optimization of deep brain stimulation parameters in the context of cloud computing with machine learning classification.
基金sponsored by the National Natural Science Foundation of China (Grant No. 41174114)the National Natural Science Foundation of China and China Petroleum & Chemical Corporation Co-funded Project (No. 40839905)
文摘Deconvolution denoising in the f-x domain has some defects when facing situations like complicated geology structure, coherent noise of steep dip angles, and uneven spatial sampling. To solve these problems, a new filtering method is proposed, which uses the generalized S transform which has good time-frequency concentration criterion to transform seismic data from the time-space to time-frequency-space domain （t-f-x）. Then in the t-f-x domain apply Empirical Mode Decomposition （EMD） on each frequency slice and clear the Intrinsic Mode Functions （IMFs） that noise dominates to suppress coherent and random noise. The model study shows that the high frequency component in the first IMF represents mainly noise, so clearing the first IMF can suppress noise. The EMD filtering method in the t-f-x domain after generalized S transform is equivalent to self-adaptive f-k filtering that depends on position, frequency, and truncation characteristics of high wave numbers. This filtering method takes local data time-frequency characteristic into consideration and is easy to perform. Compared with AR predictive filtering, the component that this method filters is highly localized and contains relatively fewer low wave numbers and the filter result does not show over-smoothing effects. Real data processing proves that the EMD filtering method in the t-f-x domain after generalized S transform can effectively suppress random and coherent noise of steep dips.
基金supported by Central Public-interest Scientific Institution Basal Research Fund (No. DQJB09B07)Knowledge Innovation Program of the Chinese Academy of Sciences under grant No. KZCX2-YW-116-1+1 种基金supported partially by National Natural Science Foundation of China (Nos. 40874095, 40730318 and 41004019)China Earthquake Administration Special Program Fund (Nos. 200808078 and 200808002)
文摘Long-time cross correlation of ambient noise has been proved as a powerful tool to extract Green＇s function between two receivers. The study of composition of ambient noise is important for a better understanding of this method. Previous studies confirm that ambient noise in the long period （3 s and longer） mostly consists of surface wave, and 0.25-2.5 s noise consists more of body waves. In this paper, we perform cross correlation processing at much higher frequency （30-70 Hz） using ambient noise recorded by a small aperture array. No surface waves emerge from noise correlation function （NCF）, but weak P waves emerge. The absence of surface wave in NCF is not due to high attenuation since surface waves are strong from active source, therefore probably the high ambient noise mostly consists of body wave and lacks surface wave. Origin of such high frequency body waves in ambient noise remains to be studied.
基金supported by Chinese Acadmy of Sciences Fund(No.KCZX-YW-116-1)Joint Seismological Science Fundation of China (Nos.20080878 and 200708035)
文摘Because ambient seismic noise provides estimated Green’s function （EGF） between two sites with high accuracy, Rayleigh wave propagation along the path connecting the two sites is well resolved. Therefore, earthquakes which are close to one seismic station can be well located with calibration extracting from EGF. We test two algorithms in locating the 1998 Zhangbei earthquake, one algorithm is waveform-based, and the other is traveltime-based. We first compute EGF between station ZHB （a station about 40 km away from the epicenter） and five IC/IRIS stations. With the waveform-based approach, we calculate 1D synthetic single-force Green’s functions between ZHB and other four stations, and obtain traveltime corrections by correlating synthetic Green’s functions with EGFs in period band of 10–30 s. Then we locate the earthquake by minimizing the differential travel times between observed earthquake waveform and the 1D synthetic earthquake waveforms computed with focal mechanism provided by Global CMT after traveltime correction from EGFs. This waveform-based approach yields a location which error is about 13 km away from the location observed with InSAR. With the traveltime-based approach, we begin with measuring group velocity from EGFs as well as group arrival time on observed earthquake waveforms, and then locate the earthquake by minimizing the difference between observed group arrival time and arrival time measured on EGFs. This traveltime-based approach yields accuracy of 3 km, Therefore it is feasible to achieve GT5 （ground truth location with accuracy 5 km） with ambient seismic noises. The less accuracy of the waveform-based approach was mainly caused by uncertainty of focal mechanism.
基金supported by the National Natural Science Foundation of China (No. 40674027)CAS outstanding 100 research program,MOST program 2007FY220100
文摘The method of extracting Green＇s function between stations from cross correlation has proven to be effective theoretically and experimentally. It has been widely applied to surface wave tomography of the crust and upmost mantle. However, there are still controversies about why this method works. Snieder employed stationary phase approximation in evaluating contribution to cross correlation function from scatterers in the whole space, and concluded that it is the constructive interference of waves emitted by the scatterers near the receiver line that leads to the emergence of Green＇s function. His derivation demonstrates that cross correlation function is just the convolution of noise power spectrum and the Green＇s function. However, his derivation ignores influence from the two stationary points at infinities, therefore it may fail when attenuation is absent. In order to obtain accurate noise-correlation function due to scatters over the whole space, we compute the total contribution with numerical integration in polar coordinates. Our numerical computation of cross correlation function indicates that the incomplete stationary phase approximation introduces remarkable errors to the cross correlation function, in both amplitude and phase, when the frequency is low with reasonable quality factor Q. Our results argue that the dis- tance between stations has to be beyond several wavelengths in order to reduce the influence of this inaccuracy on the applications of ambient noise method, and only the station pairs whose distances are above several （〉5） wavelengths can be used.
